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Developing a multi stage predicting system for corporate credit rating in emerging markets : Jordanian case

Al-Najjar, Basil and Al-Najjar, Dana (2014) Developing a multi stage predicting system for corporate credit rating in emerging markets : Jordanian case. Journal of Enterprise Information Management. ISSN 1741-0398

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Abstract

Purpose
– The purpose of this paper is to build a neural network system to predict corporate credit rating in Jordanian non-financial firms, using 19 different financial characteristics such as profitability, leverage ratios, liquidity, bankruptcy, and sales performance.

Design/methodology/approach
– The study adopts two neural network techniques namely, Kohonen network and Back Propagation Neural Network (BPNN). Our sample includes the manufacturing firms that have provided the required financial information for the period from 2000 to 2007.

Findings
– BPNN has successfully predicted firms with high performance gaining A rating and the bankrupted firms with D rating for the period from 2005 to 2007.

Originality/value
– This study is the first study to investigate credit rating in Jordan using Neural Network technique.

Item Type: Article
Uncontrolled Keywords: Neural network, Jordan, credit ratings, default risk
Subjects: H Social Sciences > HG Finance
Schools: Huddersfield Business School
Related URLs:
Depositing User: Basil Al-Najjar
Date Deposited: 14 Aug 2017 07:42
Last Modified: 14 Aug 2017 07:42
URI: http://eprints.hud.ac.uk/id/eprint/32798

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